import matplotlib.pyplot as plt
import  numpy as np
from sklearn import datasets,linear_model,discriminant_analysis,cross_validation
from sklearn.model_selection import GridSearchCV

from sklearn.model_selection import train_test_split


def load_data():
    diabetes = datasets.load_diabetes()
    return train_test_split(diabetes.datasets,diabetes.target,test_size=0.25,random_state=0)

def test_LinearRegression(*data):
    X_train,X_test,y_train,y_test = data
    regr = linear_model.LinearRegression()
    regr.fit(X_train,y_train)
    print 'Coefficients:%s,intercept %.2f'%(regr.coef_,regr.intercept_)
    print 'Residual sum of squares: %.2f' % np.mean((regr.predict(X_test)-y_test)**2)
    print 'Score: %.2f' % regr.score(X_test,y_test)
if __name__=='__main__':
    X_train,X_test,y_train,y_test = load_data()
    test_LinearRegression(X_train,X_test,y_train,y_test)